Learn Apollo, P5 and Python

Neural networks, with Keras, bring powerful machine learning to Python applications. They can answer questions like “How much traffic will hit my website tonight?” or answer classification questions like “Will this customer buy our product?” or “Will the stock price go up or down tomorrow?”

In this course, we’ll build a fully connected neural network with Keras. This is the most basic type of neural network you can create, but it’s powerful in application and can jumpstart your exploration of other frameworks. 

We’ll start the course by creating the primary network. Then we’ll:

- build and configure the network, then evaluate and test the accuracy of each
- save the model and learn how to load it and use it to make predictions in the future
- expose the model as part of a tiny web application that can be used to make predictions

You don’t need to know a lot of Python for this course, but some basic Python knowledge will be helpful. Enjoy!

Python is a widely used dynamically typed programming language. It allows for many different programming paradigms including object-oriented, imperative, functional programming, and procedural styles.

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Fully Connected Neural Networks with Keras

GraphQL is a fan favorite for good reason. It lets a client make specific, complex, and/or aggregate queries for data, and it’s user-friendly to boot.

If you’ve been meaning to learn GraphQL and start harnessing its powers, this is a great place to start.

This course is for GraphQL newbies with a basic understanding of React. It focuses on the client-side implementation of GraphQL usage using the Apollo client.

We’ll start with a guide on how to add the Apollo client to an existing project, then move on using the Query and Mutation components to fetch and manipulate data using a GraphQL API.

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

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GraphQL Data in React with Apollo Client

In Introduction to Python, we will start at the beginning: Installing python 3 and using virtual environments. With a working environment, we will learn how to manipulate strings and numbers, and gain working knowledge of data structures and flow control. We will build on that by introducing modules and classes and learn how to interact with our python applications using command line switches, console input and files.

At the end of this course, you’ll have a great working knowledge of Python, fully capable of creating your own Python projects from scratch or jumping into an existing application with the capability to read, understand, and contribute to the application.

Check out these [**community notes for this course on Github**](https://github.com/eggheadio-projects/introduction-to-the-python-3-programming-language-notes).

Introduction to the Python 3 Programming Language

Artificial intelligence. Machine learning. Bots. Computers learning and communicating with us to do our bidding. But, where do you start? How do you get a machine to even begin to understand what you speak or type at it? There are several common machine learning algorithms that will help us begin to answer these questions.

In this course we’ll learn about common machine learning algorithms that don’t require implementing a neural network. We will not be going too much into the math behind them, but instead learn what each algorithm is good for, and how to train them. We'll also learn about a few metrics for evaluating models.

We’ll implement these in Python using `scikit-learn` using `scikit-learn`’s built-in data sets. The focus of this course is on implementation and a high-level understanding of these algorithms. 

We'll look at a few ways to evaluate our models, for both classification and regression models. We'll touch on mean squared error and coefficient of determination (for regression), and accuracy score, logarithmic loss, confusion matrices, and classification reports (for classification). 

Python 2.7 is used in the lesson videos but the code provided has Python 3 available. The only breaking change is the `print` statement API.

For additional information on installation, vocabulary, and common errors visit the `README.md` to the course code attached to each lesson.

Simple and efficient tools for data mining and data analysis

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Introductory Machine Learning Algorithms in Python with scikit-learn

AWS Amplify allows developers to create, configure, and deploy Serverless APIs and functions directly from their front-end environment.In this collection, you'll learn how to deploy various types of APIs and functions using the Amplify CLI. You'll also learn how to share code among various functions using Lambda layers and schedule functions to run at an interval to implement Serverless cron jobs.

JavaScript® (often shortened to JS) is a lightweight, interpreted, object-oriented language with first-class functions, most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic, and supports object-oriented, imperative, and functional programming styles.

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Up and Running with AWS Amplify Functions

Learn how to create tuples in Python. The videos in this collection will also cover more advanced features of tuples

The Ins and Outs of Python Tuples

Apollo provides a universal GraphQL API on top of your existing services, so you can build new application features fast without waiting on backend changes.

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To query a GraphQL API, all you need to do is send an HTTP request that includes the query operation in the body of the request. In this lesson, we will use the browser’s fetch method to request the total days skied from our GraphQL API.

Fetch Data from a GraphQL API

Apollo Server is a GraphQL server that listens for incoming HTTP requests on a single endpoint.  In this lesson, we will stand up a simple GraphQL service that handles a query for total days skied during a season.

Create a GraphQL API with Apollo Server 2.0

Created by the team at Prisma, graphql-request is a lightweight package that can be used to send queries to any GraphQL API. Sending a request with graphql-request uses less syntax than a fetch request. In this lesson, we will query the totalDays field using this helper package.

Query a GraphQL API with graphql-request

Apollo Client allows you to build performant, production-ready applications that consume data from GraphQL services. In this lesson, we will query the totalDays field using Apollo Client.

Send a GraphQL Query with Apollo Client

React Apollo is a component library that we can use to rapidly build GraphQL client applications with React. In this lesson, we get our React app ready by setting up the Apollo Provider and sending our query using the Query component.

Set Up a React GraphQL Client Application with react-apollo

The Query component is used to render the state of the network request along with the data that is returned from the GraphQL API. In this lesson, we will refactor our application to include an App component that displays the resulting count returned by the totalDays field.

Display Query Results using the Query Component 

Queries get data from GraphQL services. If we want to change data, we will use GraphQL mutations. In this lesson, we’ll look at how to design GraphQL mutations to increment or decrement the number of ski days on record.

Change Data with GraphQL Mutations

We can read data from and write data to the cache directly with Apollo Client. In this video, we’ll update the UI by interacting with the cache instead of sending an additional request to the GraphQL server.

Update the Apollo Local Cache with the readQuery and writeQuery Methods

Using the GraphQL Schema Definition Language, we can define types that reflect all of the objects available on our API. In this lesson, we will create a SkiDay type and return a list of SkiDay objects with an allDays query. We will also create an enum, which describes a restricted list of allowed values for a particular field.

Create a GraphQL Object Type and Query a List of Objects

The addDay mutation should add details about each ski day. In this lesson, we’ll capture argument values from the GraphQL mutation and use this to change the ski day array.

Add Data to an Array with a GraphQL Mutation

Resolvers are functions that return data for specific fields. In this lesson, we’ll take a look at how to throw errors within resolvers if the data passed as arguments is incorrect or insufficient.

Incorporate Custom Error Handling within GraphQL Resolvers

GraphQL has five built-in scalar types that can be returned from a field: Int, Float, Boolean, String, and ID. It is also possible to create and validate your own custom scalar if you want to return a single value or leaf instead of an object from a field. In this lesson, we’ll build a custom scalar type to handle parsing and serializing dates.

Define a Custom Scalar Type for a GraphQL API

If you want to be able to parse and serialize custom scalar types sent as arguments, you’ll add the parseValue and parseLiteral functions to the custom scalar constructor. In this video, we’ll take a closer look at these functions and how they can be used to transform data passed by the client.


Parsing GraphQL Mutation Arguments with Custom Scalars

When passing arguments to a GraphQL mutation, you can send them inline, or you can wrap them in an input type. In this lesson, we’ll create an input type for the addDay mutation which will allow us to pass an entire object as an argument.

Wrap GraphQL Mutation Arguments with a GraphQL Input Type

GraphQL mutations are used to change data and can be also used to delete data. In this lesson, we’ll make changes to the removeDay mutation to delete a day from the ski days array by id. Additionally, we’ll return a custom type when we send the mutation.

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